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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

SIMPA

SIMPA (Spatially Integrated Multivariate Probabilistic Assessment) is a Python-based fuzzy logic tool designed to help assess the likelihood of fluid and/or gas migration pathways throughout the subsurface. The SIMPA tool helps users develop and apply fuzzy logic to various datasets to construct knowledge-based inferential rules that reduce uncertainty and results in a visual representation depicting the likelihood of potential fluid and/or gas migration pathways. SIMPA results can offers an understanding of the magnitude and extent of natural and anthropogenic subsurface pathways, offering insight to subsurface hazards to improve storage assessments and critical information for improving industry decisions related to the use of various CCS methods and technologies. In addition, SIMPA can offer new insights for areas with little to no data to help inform site selection and production, evaluate potential risks and hazards, and support various decision making and risk management needs.

carbon storage↗
NASA NTRS2019

Satellite-Based Assessment of Grassland Conversion and Related Fire Disturbance in the Kenai Peninsula, Alaska

Spruce beetle-induced (Dendroctonus rufipennis (Kirby)) mortality on the Kenai Peninsula has heightened local wildfire risk as canopy loss facilitates the conversion from bare to fire-prone grassland. We collected images from NASA satellite-based Earth observations to visualize land cover succession at roughly five-year intervals following a severe, mid-1990's beetle infestation to the present. We classified these data by vegetation cover type to quantify grassland encroachment patterns over time. Raster band math provided a change detection analysis on the land cover classifications. Results indicate the highest wildfire risk is linked to herbaceous and black spruce land cover types, The resulting land cover change image will give the Kenai National Wildlife Refuge (KENWR) ecologists a better understanding of where forests have converted to grassland since the 1990s. These classifications provided a foundation for us to integrate digital elevation models (DEMs), temperature, and historical fire data into a model using Python for assessing and mapping changes in wildfire risk. Spatial representations of this risk will contribute to a better understanding of ecological trajectories of beetle-affected landscapes, thereby informing management decisions at KENWR.

Risk modeling↗
DOE OSTI2016

Integrated PET/MR breast cancer imaging: Attenuation correction and implementation of a 16-channel RF coil

Purpose: This study aims to develop, implement, and evaluate a 16-channel radiofrequency (RF) coil for integrated positron emission tomography/magnetic resonance (PET/MR) imaging of breast cancer. The RF coil is designed for optimized MR imaging performance and PET transparency and attenuation correction (AC) is applied for accurate PET quantification. Methods: A 16-channel breast array RF coil was designed for integrated PET/MR hybrid imaging of breast cancer lesions. The RF coil features a lightweight rigid design and is positioned with a spacer at a defined position on the patient table of an integrated PET/MR system. Attenuation correction is performed by generating and applying a dedicated 3D CT-based template attenuation map. Reposition accuracy of the RF coil on the system patient table while using the positioning frame was tested in repeated measurements using MR-visible markers. The MR, PET, and PET/MR imaging performances were systematically evaluated using modular breast phantoms. Attenuation correction of the RF coil was evaluated with difference measurements of the active breast phantoms filled with radiotracer in the PET detector with and without the RF coil in place, serving as a standard of reference measurement. The overall PET/MR imaging performance and PET quantification accuracy of the new 16-channel RF coil and its AC were then evaluated in first clinical examinations on ten patients with local breast cancer. Results: The RF breast array coil provides excellent signal-to-noise ratio and signal homogeneity across the volume of the breast phantoms in MR imaging and visualizes small structures in the phantoms down to 0.4 mm in plane. Difference measurements with PET revealed a global loss and thus attenuation of counts by 13% (mean value across the whole phantom volume) when the RF coil is placed in the PET detector. Local attenuation ranging from 0% in the middle of the phantoms up to 24% was detected in the peripheral regions of the phantoms at positions closer to attenuating hardware structures of the RF coil. The position accuracy of the RF coil on the patient table when using the positioning frame was determined well below 1 mm for all three spatial dimensions. This ensures perfect position match between the RF coil and its three-dimensional attenuation template during the PET data reconstruction process. When applying the CT-based AC of the RF coil, the global attenuation bias was mostly compensated to ±0.5% across the entire breast imaging volume. The patient study revealed high quality MR, PET, and combined PET/MR imaging of breast cancer. Quantitative activity measurements in all 11 breast cancer lesions of the ten patients resulted in increased mean difference values of SUV{sub max} 11.8% (minimum 3.2%; maximum 23.2%) between nonAC images and images when AC of the RF breast coil was applied. This supports the quantitative results of the phantom study as well as successful attenuation correction of the RF coil. Conclusions: A 16-channel breast RF coil was designed for optimized MR imaging performance and PET transparency and was successfully integrated with its dedicated attenuation correction template into a whole-body PET/MR system. Systematic PET/MR imaging evaluation with phantoms and an initial study on patients with breast cancer provided excellent MR and PET image quality and accurate PET quantification.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Risso's dolphins plan foraging dives

ABSTRACT Humans remember the past and use that information to plan future actions. Lab experiments that test memory for the location of food show that animals have a similar capability to act in anticipation of future needs, but less work has been done on animals foraging in the wild. We hypothesized that planning abilities are critical and common in breath-hold divers who adjust each dive to forage on prey varying in quality, location and predictability within constraints of limited oxygen availability. We equipped Risso's dolphins with sound-and-motion recording tags to reveal where they focus their attention through their externally observable echolocation and how they fine tune search strategies in response to expected and observed prey distribution. The information from the dolphins was integrated with synoptic prey data obtained from echosounders on an underwater vehicle. At the start of the dives, whales adjusted their echolocation inspection ranges in ways that suggest planning to forage at a particular depth. Once entering a productive prey layer, dolphins reduced their search range comparable to the scale of patches within the layer, suggesting that they were using echolocation to select prey within the patch. On ascent, their search range increased, indicating that they decided to stop foraging within that layer and started searching for prey in shallower layers. Information about prey, learned throughout the dive, was used to plan foraging in the next dive. Our results demonstrate that planning for future dives is modulated by spatial memory derived from multi-modal prey sampling (echoic, visual and capture) during earlier dives.

Arranz, Patricia↗
NASA NTRS1989

Detection of edges using local geometry

Researchers described a new representation, the local geometry, for early visual processing which is motivated by results from biological vision. This representation is richer than is often used in image processing. It extracts more of the local structure available at each pixel in the image by using receptive fields that can be continuously rotated and that go to third order spatial variation. Early visual processing algorithms such as edge detectors and ridge detectors can be written in terms of various local geometries and are computationally tractable. For example, Canny's edge detector has been implemented in terms of a local geometry of order two, and a ridge detector in terms of a local geometry of order three. The edge detector in local geometry was applied to synthetic and real images and it was shown using simple interpolation schemes that sufficient information is available to locate edges with sub-pixel accuracy (to a resolution increase of at least a factor of five). This is reasonable even for noisy images because the local geometry fits a smooth surface - the Taylor series - to the discrete image data. Only local processing was used in the implementation so it can readily be implemented on parallel mesh machines such as the MPP. Researchers expect that other early visual algorithms, such as region growing, inflection point detection, and segmentation can also be implemented in terms of the local geometry and will provide sufficiently rich and robust representations for subsequent visual processing.

Gualtieri, J. A.↗
NASA NTRS2009

Head Worn Display System for Equivalent Visual Operations

Head-Worn Displays or so-called, near-to-eye displays have potentially significant advantages in terms of cost, overcoming cockpit space constraints, and for the display of spatially-integrated information. However, many technical issues need to be overcome before these technologies can be successfully introduced into commercial aircraft cockpits. The results of three activities are reported. First, the near-to-eye display design, technological, and human factors issues are described and a literature review is presented. Second, the results of a fixed-base piloted simulation, investigating the impact of near to eye displays on both operational and visual performance is reported. Straight-in approaches were flown in simulated visual and instrument conditions while using either a biocular or a monocular display placed on either the dominant or non-dominant eye. The pilot's flight performance, visual acuity, and ability to detect unsafe conditions on the runway were tested. The data generally supports a monocular design with minimal impact due to eye dominance. Finally, a method for head tracker system latency measurement is developed and used to compare two different devices.

Cupero, Frank↗
NASA NTRS2022

An Earth System Digital Twin for Flood Prediction and Analysis

An Earth System Digital Twin (ESDT) is a dynamic, interactive, digital replica of the state and temporal evolution of Earth systems. It integrates multiple models along with observation data, and connecting them with analysis, AI, and visualization tools. Together, these enable users to explore the current state of the Earth system, predict future conditions, and run hypothetical scenarios to understand how the system would evolve under various assumptions. The NASA’s Advanced Information Systems Technology (AIST)’s Integrated Digital Earth Analysis System (IDEAS) project is to establish an extensible architectural solution to develop digital twins of our physical environment for Earth Science. IDEAS delivers a formal system architecture with mechanisms for the outputs of one model to feed into others; for driving models with observation data; and for harmonizing observation data and model outputs for analysis. To validate and demonstrate the IDEAS architecture, this project collaborates with the Space Climate Observatory (SCO)’s FloodDAM project and the Centre National d’Etudes Spatiales (CNES) to focus on floods detection, prediction and their impacts.

Kettig, Peter↗
NASA NTRS2003

NASA Tech Briefs, November 2003

Topics covered include: Computer Program Recognizes Patterns in Time-Series Data; Program for User-Friendly Management of Input and Output Data Sets; Noncoherent Tracking of a Source of a Data-Modulated Signal; Software for Acquiring Image Data for PIV; Detecting Edges in Images by Use of Fuzzy Reasoning; A Timer for Synchronous Digital Systems; Prototype Parts of a Digital Beam-Forming Wide-Band Receiver; High-Voltage Droplet Dispenser; Network Extender for MIL-STD-1553 Bus; MMIC HEMT Power Amplifier for 140 to 170 GHz; Piezoelectric Diffraction-Based Optical Switches; Numerical Modeling of Nanoelectronic Devices; Organizing Diverse, Distributed Project Information; Eigensolver for a Sparse, Large Hermitian Matrix; Modified Polar-Format Software for Processing SAR Data; e-Stars Template Builder; Software for Acoustic Rendering; Functionally Graded Nanophase Beryllium/Carbon Composites; Thin Thermal-Insulation Blankets for Very High Temperatures; Prolonging Microgravity on Parabolic Airplane Flights; Device for Locking a Control Knob; Cable-Dispensing Cart; Foam Sensor Structures Would be Self-Deployable and Survive Hard Landings; Real-Gas Effects on Binary Mixing Layers; Earth-Space Link Attenuation Estimation via Ground Radar Kdp; Wedge Heat-Flux Indicators for Flash Thermography; Measuring Diffusion of Liquids by Common-Path Interferometry; Zero-Shear, Low-Disturbance Optical Delay Line; Whispering-Gallery Mode-Locked Lasers; Spatial Light Modulators as Optical Crossbar Switches; Update on EMD and Hilbert-Spectra Analysis of Time Series; Quad-Tree Visual-Calculus Analysis of Satellite Coverage; Dyakonov-Perel Effect on Spin Dephasing in n-Type GaAs; Update on Area Production in Mixing of Supercritical Fluids; and Quasi-Sun-Pointing of Spacecraft Using Radiation Pressure.

Source record↗
NASA NTRS2018

Overview of the Digitization Workflow Post Image Acquisition of Apollo Lunar and Antarctic Meteorite Samples Using Agisoft Photoscan for the NASA 3D Astromaterials Virtual Samples Collection

The 3D Virtual Astromaterials Samples (3DVAS) collection is a multi-year funded project to create a digital database of sixty Apollo Lunar and Antarctic Meteorite samples following non-destructive documentation conservation protocols. After initial image processing, the photos are evaluated and processed using unique structure-from-motion photogrammetric techniques in a high performance modelling software designed to create a 3D model from 2D images: Agisoft Photoscan Pro. Agisoft Photoscan Pro uses image processing algorithms and techniques originating in computer vision to resolve 3D models for accurate and detailed visualization of a subject. The software provides a stepwise process that is tailored per model based on spatial and specular reflectance properties, for example. The process includes: photo alignment, creation of a dense point cloud, mesh, and finally texture. Photo alignment is dependent on model properties. The 3DVAS process requires a special rotation platform with calibrated photogrammetric targets, specific distance rotation protocols, and a contrasting background for alignment and scale accuracy. As a result of the photographic process, alignment will complete with two mirrored hemispheres that, in a sense, represent the 2D images overlapping to create a 3D model. Each dense point cloud is analyzed with provided statistical measures in a gradual selection process to eliminate outliers. The point cloud is reduced to include only data valuable to the final model. When a precise dense point cloud is achieved, a mesh and texture are applied. Each model is scaled with scale bar accuracies within 100 microns. Each sample has its own intimate process for modelling; there is no standard for the parameters required in the final creation of a high resolution model. By processing multiple samples, a skill is gained in practice to allow a close definition of the original sample and will result in the most detailed version of the sample shell. This process completes one-fifth of the 3DVAS protocol for providing accurate digital documentation. Each model shell is merged with X-ray Computed Tomography data to create a full volumetric sample. All 3DVAS data will be served on NASA's Astromaterials Acquisition and Curation website with an early subset of data available in 2019 and the 3D Virtual Astromaterials Samples Collection launch in 2020.

Thomas, Andi B.↗
NASA NTRS2017

Airborne Hyperspectral Sensing of Monitoring Harmful Algal Blooms in the Great Lakes Region: System Calibration and Validation

Harmful algal blooms (HABs) in Lake Erie have been prominent in recent years. The bloom in 2014 reached a severe level causing the State of Ohio to declare a state of emergency. At that time NASA Glenn Research Center was requested by stakeholders to help monitor the blooms in Lake Erie. Glenn conducted flights twice a week in August and September and assembled and distributed the HAB information to the shoreline water resource managers using its hyperspectral imaging sensor (in development since 2006), the S􀂱3 Viking aircraft, and funding resources from the NASA Headquarters Earth Science Division. Since then, the State of Ohio, National Oceanic and Atmospheric Administration (NOAA), and U.S. Environmental Protection Agency (EPA) have elevated their funding and activities for observing, monitoring, and addressing the root cause of HABs. Also, the communities and stakeholders have persistently requested NASA Glenn􀂶s participation in HAB observation. Abundant field campaigns and sample analyses have been funded by Ohio and NOAA, which provided a great opportunity for NASA to advance science and airborne hyperspectral remote sensing economically. Capitalizing on this opportunity to advance the science of algal blooms and remote sensing, NASA Glenn conducted the Airborne Hyperspectral Observation of harmful algal blooms campaign in 2015 that was, in many respects, twice as large as the 2014 campaign. Focusing mostly on Lake Erie, but also including other small inland lakes and the Ohio River, the campaign was conducted in partnership with a large number of partners specializing in marine science and remote sensing. Airborne hyperspectral observation of HABs holds promise to distinguish potential HABs from nuisance blooms, determine their concentrations, and delineate their movement in an augmented spatial and temporal resolution and under clouds􀂲all of which are excellent complements to satellite observations. Working with collaborators at several Ohio and Michigan institutions as well as one in South Dakota and one in Alabama, this effort was able to provide next-day georeferenced estimates of cyanobacteria and scum concentrations. Very prompt processing and analysis of the hyperspectral imagery is necessary for the information to be acted upon. For example, a next-day report of an overflight over the Ohio River indicated that a bloom could be present as far downstream as the Cincinnati intake, but the Ohio EPA had not received visual reports of a bloom that far downstream. Water samples were obtained at the Cincinnati water intake, based on the flight data, and detected microcystins in the source water. The flight data helped State and municipal authorities realize the potential extent of that bloom, and triggered response sampling, before the visual river-wide scums started forming. The present document describes the process that was utilized to take raw remote sensing data and create information products; this includes system calibration and validation, efforts to correct atmospheric effects, and algorithms that produce the data products. Furthermore, successful research into improved algorithms for expanding the capability to delineate in water constituents is included. Finally, comparisons that show expected relationships between ground-based measurements and hyperspectral imager version 2 (HSI2) data results are presented, giving confidence in the remote sensing products.

Hyperspectral Imaging↗
NASA NTRS2012

Evaluations of Thin Cirrus Contamination and Screening in Ground Aerosol Observations Using Collocated Lidar Systems

Cirrus clouds, particularly sub visual high thin cirrus with low optical thickness, are difficult to be screened in operational aerosol retrieval algorithms. Collocated aerosol and cirrus observations from ground measurements, such as the Aerosol Robotic Network (AERONET) and the Micro-Pulse Lidar Network (MPLNET), provide us with an unprecedented opportunity to examine the susceptibility of operational aerosol products to thin cirrus contamination. Quality assured aerosol optical thickness (AOT) measurements were also tested against the CALIPSO vertical feature mask (VFM) and the MODIS-derived thin cirrus screening parameters for the purpose of evaluating thin cirrus contamination. Key results of this study include: (1) Quantitative evaluations of data uncertainties in AERONET AOT retrievals are conducted. Although AERONET cirrus screening schemes are successful in removing most cirrus contamination, strong residuals displaying strong spatial and seasonal variability still exist, particularly over thin cirrus prevalent regions during cirrus peak seasons, (2) Challenges in matching up different data for analysis are highlighted and corresponding solutions proposed, and (3) Estimation of the relative contributions from cirrus contamination to aerosol retrievals are discussed. The results are valuable for better understanding and further improving ground aerosol measurements that are critical for aerosol-related climate research.

Huang, Jingfeng↗
NASA NTRS2011

Straight Ahead in Microgravity

INTRODUCTION The subjective straight-ahead direction is a very basic perceptual reference for spatial orientation and locomotion. The perceived straight-ahead along the horizontal and vertical meridian is largely determined by both otolith and somatosensory inputs which are altered in microgravity. The Straight Ahead in Microgravity (SAM) experiment will be conducted on the International Space Station (ISS) to examine how this spatial processing changes as a function of spaceflight. METHODS Data will be collected before the flight, at one-month intervals during long-duration stay (180 days) on board ISS, and after return to Earth. Control studies will also be performed during parabolic flights. Three different protocols will be used in each test session: (1) Fixation: The subject will be asked to look at actual targets (normal vision) and then to imagine these same targets (occluded vision) in the straight-ahead direction. Targets will be located at near distance (arm s length, ~0.5m), medium distance (~1 m), and far distance (beyond 2 m). This task will be successively performed with subject s body aligned with the spacecraft interior, and with subject s body tilted forward and backward by an operator. (2) Saccades: The subject will be asked to make horizontal and vertical saccades, first relative to the spacecraft interior reference system, and then relative to the subject s head reference system. This task will be successively performed with subject s body aligned with the spacecraft interior, and with subject s body tilted in roll or in pitch by an operator. (3) Linear Vestibulo-Ocular Reflex (VOR): The subject will be asked to stare at actual visual targets (normal vision) at various distances (near, medium, far) in the straight-ahead direction. Vision will then be occluded, and the subject will be asked to continue staring at the same imagined targets while he/she is passively translated forward-backward, up-down, or side-to-side. The subject's body motion will be performed by the restrained operator while the subject is free-floating. EXPECTED RESULTS The coupling of downward gaze with vergence eye movements observed on Earth is expected to increase in microgravity. Saccadic eye movements made in darkness along perceived axes are expected to be more closely aligned with the body s longitudinal axis in 0g compared to 1g, as the reference system for spatial orientation moves from an allocentric (gravitational) to an egocentric (idiotropic) vector. Changes in the linear VOR will reflect adaptive changes in otolith-ocular reflex contributions to the perceived straight-ahead. DISCUSSION A change in an individual's egocentric reference might have negative consequences on evaluating the direction of an approaching object or on the accuracy of reaching movements or locomotion. Consequently, investigating how microgravity affects the egocenter is important for understanding the problems associated with long-term effects of microgravity on astronauts' and how they re-adapt to the return of gravitational forces on Earth or other planetary surfaces. This project therefore has theoretical, practical and even clinical implications for the sensorimotor research gap "What are the changes in sensorimotor function over the course of a mission?"

Clement, G.↗
DOE OSTI2015

TU-CD-207-08: Intrinsic Image Quality Comparison of Synthesized 2-D and FFDM Images

Purpose: With the combined interest of managing patient dose, maintaining or improving image quality, and maintaining or improving the diagnostic utility of mammographic data, this study aims to compare the intrinsic image quality of Hologic’s synthesized 2-D (C-View) and 2-D FFDM images in terms of resolution, contrast, and noise. Methods: This study utilized a novel 3-D printed anthropomorphic breast phantom in addition to the American College of Radiology (ACR) mammography accreditation phantom. Analysis of the 3-D anthropomorphic phantom included visual assessment of resolution and analysis of the normalized noise power spectrum. Analysis of the ACR phantom included both visual inspection and objective automated analysis using in-house software. The software incorporates image- and object-specific CNR visibility thresholds which account for image characteristics such as noise texture which affect object visualization. T- test statistical analysis was also performed on ACR phantom scores. Results: The spatial resolution of C-View images is markedly lower (at least 50% worse) than that of FFDM. And while this is generally associated with the benefit of reduced relative noise magnitude, the noise in C-View images tends to have a more mottled (predominantly low-frequency) texture. In general, for high contrast objects, C-View provides superior visualization over FFDM; however this benefit diminishes for low contrast objects and is applicable only to objects that are sufficiently larger than the spatial resolution threshold. Based on both observer and automated ACR phantom analysis, between 50–70% of C-View images failed to meet ACR minimum accreditation requirements – primarily due to insufficient (unbroken) fiber visibility. Conclusion: Compared to FFDM, C-View offers better depiction of objects of certain size and contrast, but provides poorer overall resolution and noise properties. Based on these findings, the utilization of C-View images in the clinical setting requires careful consideration, especially if considering the discontinuation of FFDM imaging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Simulation of X-ray transient absorption for following vibrations in coherently ionized F 2 molecules

We report femtosecond and attosecond X-ray transient absorption experiments are becoming increasingly sophisticated tools for probing nuclear dynamics. In this work, we explore and develop theoretical tools needed for interpretation of such spectra,in order to characterize the vibrational coherences that result from ionizing a molecule in a strong IR field. Ab initio data for F 2 is combined with simulations of nuclear dynamics, in order to simulate time-resolved X-ray absorption spectra for vibrational wavepackets after coherent ionization at 0 K and at finite temperature. Dihalogens pose rather difficult electronic structure problems, and the issues encountered in this work will be reflective of those encountered with any core–valence excitation simulation when a bond is breaking. The simulations reveal a strong dependence of the X-ray absorption maximum on the locations of the vibrational wave packets. A Fourier transform of the simulated signal shows features at the overtone frequencies of both the neutral and the cation, which reflect spatial interferences of the vibrational eigenstates. This provides a direct path for implementing ultrafast X-ray spectroscopic methods to visualize coherent nuclear dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Volumetric Rendering on Wavelet-Based Adaptive Grid

Numerical modeling of physical phenomena frequently involves processes across a wide range of spatial and temporal scales. In the last two decades, the advancements in wavelet-based numerical methodologies to solve partial differential equations, combined with the unique properties of wavelet analysis to resolve localized structures of the solution on dynamically adaptive computational meshes, make it feasible to perform large-scale numerical simulations of a variety of physical systems on a dynamically adaptive computational mesh that changes both in space and time. Volumetric visualization of the solution is an essential part of scientific computing, yet the existing volumetric visualization techniques do not take full advantage of multi-resolution wavelet analysis and are not fully tailored for visualization of a compressed solution on the wavelet-based adaptive computational mesh. Our objective is to explore the alternatives for the visualization of time-dependent data on space-time varying adaptive mesh using volume rendering while capitalizing on the available sparse data representation. Two alternative formulations are explored. The first one is based on volumetric ray casting of multi-scale datasets in wavelet space. Rather than working with the wavelets at the finest possible resolution, a partial inverse wavelet transform is performed as a preprocessing step to obtain scaling functions on a uniform grid at a user-prescribed resolution. As a result, a solution in physical space is represented by a superposition of scaling functions on a coarse regular grid and wavelets on an adaptive mesh. An efficient and accurate ray casting algorithm is based just on these coarse scaling functions. Additional details are added during the ray tracing by taking an appropriate number of wavelets into account based on support overlap with the interpolation point, wavelet coefficient magnitude, and other characteristics, such as opacity accumulation (front to back ordering) and deviation from frontal viewing direction. The second approach is based on complementing of wavelet-based adaptive mesh to the traditional Adaptive Mesh Refinement (AMR) mesh. Both algorithms are illustrated and compared to the existing volume visualization software for Rayleigh-Benard thermal convection and electron density data sets in terms of rendering time and visual quality for different data compression of both wavelet-based and AMR adaptive meshes.

Vezolainen, Alexei V.↗
NASA NTRS2019

Optical Flow for Intermediate Frame Interpolation of Multispectral Geostationary Satellite Data

Applications in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on spatial and temporal resolutions of satellite observations. However, there are typically trade-offs between spatial and temporal resolutions in dataset selection. For instance, geostationary weather tracking satellites are designed to take snapshots many times throughout the day but sensor hardware limits data collection. In this work we tackle this limitation, developing a method for temporal upsampling of multi-spectral satellite imagery using optical flow video interpolation deep convolutional neural networks. The presented model, extends Super SloMo (SSM) from single optical flow estimates to multichannel where flows are computed per band. We apply this technique on 8 multi-spectral bands of NOAA/NASA's GOES-16 mesoscale dataset to temporally enhance full disk hemispheric snapshots from 15 minutes to 1 minute. Through extensive experimentation, we show SSM vastly outperforms the linear interpolation baseline and that multichannel optical flows improves performance on GOES-16. A visual analysis of optical flow vectors clearly identifies hurricanes and large-scale atmospheric dynamics. Furthermore, we discuss challenges and open questions related to optical flow and temporal interpolation of multispectral geostationary satellite imagery.

Optical Flow↗
DOE OSTI2019

Cumulative Spatial Impact Layers™

Cumulative Spatial Impact Layers™ (CSIL) is a GIS-based tool that summarizes spatio-temporal datasets based on overlapping features and attributes. Applying a recursive quadtree method and multiple additive frameworks, the CSIL tool allows users to analyze raster and vector datasets simultaneously by calculating data, record, or attribute density. The CSIL tool was designed based on the original approach (Bauer et al. 2015) and more information on the tool overall along with applications can be found in Romeo et al. 2019). Providing an efficient summary of disparate geospatial data, CSIL bridges the gap between understanding data and analysis. Bauer, J. R., Nelson, J., Romeo, L., Eynard, J., Sim, L., Halama, J., Rose, K., & Graham, J. (2015). A spatio-temporal approach to analyze broad risks and potential impacts associated with uncontrolled hydrocarbon release events in the offshore Gulf of Mexico (NETL-TRS-2-2015 EPAct Technical Report Series). U.S. Department of Energy, National Energy Technology Laboratory: Morgantown, WV; p 60. Romeo, L., Nelson, J., Wingo, P., Bauer, J., Justman, D., & Rose, K. (2019). Cumulative spatial impact layers: A novel multivariate spatio-temporal analytical summarization tool. Transactions in GIS.

Multivariate Visualization↗